Machine Learning Engineer (All genders)

Description

The company builds autonomous defence platforms and AI-driven software for NATO Allies and their partners, designed for demanding environments.

The Operations Excellence team sits within the COO organization and works as an internal strategic partner to managers, team leads and colleagues. It delivers data-driven insights, leads major projects and improves processes continuously.

As an individual contributor, you own complex initiatives end to end and influence key operating decisions with cross-functional stakeholders at one of Europe's fastest-growing unicorns.

The role owns the data infrastructure and ML model work for the OAA team's AI use cases, from yield prediction on the production line to anomaly detection in financial data.

Responsibilities

• Build data pipelines that pull from operational systems (MES, ERP) and back-office sources to feed ML models
• Develop models for production and back-office use, taking them from experiments to live deployment
• Set up serving, monitoring, drift detection and retraining so models run reliably in production
• Scope and validate ML use cases with the OAA Lead and stakeholders, checking feasibility, data availability and ROI
• Work with the Automation Engineer to plug model outputs into automated workflows
• Maintain and improve live models as data and operating conditions change
• Document pipelines, model architectures, feature definitions and deployment configurations

Requirements

• 4, 7 years in data engineering or ML engineering
• Proven experience taking ML models into production, beyond research or notebook work
• Strong Python for data engineering and ML development
• Solid SQL for data extraction, validation and pipeline work
• Hands-on use of scikit-learn, PyTorch or an equivalent ML framework
• Working knowledge of MLOps: model versioning, serving, monitoring and retraining
• Experience with data pipeline tools such as Airflow, dbt or equivalent
• Experience with a cloud data platform: AWS, GCP or Azure
• Experience with industrial, time-series or back-office financial data
• MSc in Data Science, Computer Science, Statistics or an equivalent degree
• Candidates must be eligible to obtain and maintain the security clearance required for this role; details follow during recruitment
• Apply by sending your CV in English

Conditions

Due to the defence sector, candidates must be eligible to obtain and maintain the appropriate security clearance. Details are shared during the hiring process.

Benefits

• Your work protects personnel and supports European and national sovereignty.
• You will work alongside leading experts in autonomous systems, advanced propulsion and secure cyber platforms.
• The environment is fast-moving and collaborative, with serious R&D backing for new ideas.